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Last year, writer Joanna Maciejewska shared a thought that resonated with creatives (and radio programmers) everywhere: “I want AI to do my laundry and dishes so that I can do art and writing, not for AI to do my art and writing so that I can do my laundry and dishes.” It was an honest sentiment from an artist wrestling with how AI would affect her livelihood. Because as artificial intelligence grows more powerful and more present in our lives, the question isn’t just what it can do, it’s what we choose to do with it.
This is especially true in radio.
Modern AI-powered products can now schedule music, produce segues, master audio and even generate story topics or imaging elements. However, radio isn’t at its best when it’s simply “efficient” but when it’s human — when someone tells you why a song matters, a familiar voice connects with you through story, or when a station feels relevant to your daily life.
If we’re going to use AI in radio, let’s ensure we utilize it for the right purposes.
Let AI do the laundry. Let us make the radio.
Spotify’s pivot — a signal worth noting
Earlier this year, Bloomberg published a story that sparked considerable discussion in the music world: Spotify, long regarded as the gold standard in algorithmic music discovery, was making a quiet yet significant shift to put its human editors front and center again.
After years of leading with algorithmic playlists, Spotify has begun to emphasize the value and perspective of its global editorial team. Curators’ names are now featured. Playlists are being presented with more personality and voice. The company is actively reminding users that humans, rather than just data, are behind the music they’re discovering.
Why? Because the machine just isn’t very interesting.
Listeners have grown fatigued by streams that “learn” their preferences but fail to surprise or delight them. They want something that feels intentional, personal and context-rich. They want curation with a point of view.
Spotify, in its own way, is rediscovering what radio has known all along.
What radio does better
Radio has always excelled at giving music meaning. Great radio doesn’t just play the hits; instead, it weaves them into a story. It introduces artists, explains trends, shares memories and connects songs to real lives and real communities. Whether it’s a morning show in Atlanta or a late-night host in Oslo, the magic of radio has never just been about the playlist. It’s about the why.
That’s something that machine learning alone simply can’t deliver. But that doesn’t mean AI has no place in radio… far from it.
In fact, radio is uniquely positioned to benefit from AI in powerful, profitable ways.
The future belongs to the broadcasters who understand the difference between content and connection.
The right work for the right intelligence
Creating a great radio station with traditional tools involves a lot of noncreative work — building music logs, editing segues, formatting clocks, marking intros and outros, timing voice tracks, mastering audio, organizing libraries, logging metadata, and more. These tasks are essential but time-consuming and not the reason most programmers and producers got into this business.
AI is remarkably well-suited to handle them.
When used thoughtfully, AI can automate the mechanical aspects of production and programming completely. Not to replace people, but to free them. Instead of spending hours fixing transitions or marking songs to “hit the post,” radio teams can focus on what they’re great at: finding and selecting great music, crafting stories, building experiences and connecting with listeners in ways machines simply can’t.
A philosophy we stand behind
This isn’t hypothetical for us; it’s at the core of how we think at Super Hi-Fi. We believe deeply in machine learning and automation. But we believe just as deeply in intention. In a world where radio workforces have already been slashed to the bone and spread thinner than ever, our mission isn’t to automate the medium; it’s to automate the tedium so that radio can sound more human than ever.
We’ve seen firsthand how AI, when applied correctly, empowers small teams to create massive-scale radio networks that sound more local, more alive and more connected than their legacy counterparts. It enables programmers to build and test new radio formats incredibly quickly, allowing them to spend their time shaping those stations with personality, relevance and care. It allows talent to focus on being talent, not engineers. And it gives broadcasters the ability to scale quality without scaling burnout.
This isn’t about reducing headcount. It’s about increasing creativity.
Spotify’s pivot back to human curation isn’t a regression. It’s a recalibration. And for radio, it’s a moment of clarity that the future isn’t AI versus humans — it’s AI for humans.
A new model for human-AI collaboration
Here’s what we believe the new model looks like:
- AI handles the mechanics — think scheduling, mastering, production and playout; i.e., the tasks that don’t require taste, just precision;
- Humans guide the taste — choosing the music, defining the station’s voice, communicating the stories and connecting the dots;
- Technology amplifies the vision — with the right tools, one great programmer can scale across dozens of markets, delivering curated experiences that sound deeply local, personal and professional.
This model isn’t theoretical. It’s live today, and it’s working. The stations thriving right now are the ones leaning into human creativity enhanced by AI, not those stuck on creating more music logs for yet another station because more of their peers have just been laid off.
AI is here. It’s not going away. However, the question is no longer whether radio should adopt AI, but rather how.
The future belongs to the broadcasters who understand the difference between content and connection. Those who use AI to power the machine, use humans to power the meaning, and capture more margin along the way.
Let AI do the laundry. Let us make the radio.
The author is co-founder and CEO of Super Hi-Fi.
This article originally appeared in the RedTech International special publication Radio Futures 2025
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